Analytics Tutorial: How to Segment Out Time Zones & Regions

Analyze your data for particular parts of the country to make better advertising decisions

This task came up recently when we were analyzing a particular PPC campaign–one of our own, actually. We run some remarketing and display campaigns throughout the US and Canada. We are always looking for hour of the day optimization (dayparting as it was called on Madison Avenue). However, when we ran an hour of the day analysis aren’t we looking at, say, 12 noon in Chicago and 10am in California?

This would seem to muddy the data: we are looking for particular hours of the day when website conversions are strongest, and since it isn’t the same time of day everywhere on a continent, we want to separate and segment the data.

Google Analytics “Hour of Day” Report

Google Analytics Hour of Day report shows us what we need: aggregate Adwords visitor data segmented on a 24-hour graph. We’ve set the following chart with a secondary data point, the Goal Conversion Rate:

 

Of course we care about conversion rate–that’s why we run ads, to get customers to reach out to us for further consultation.

And we can see from the chart that we’ve got a mixed conversion rate throughout the day. Keep in mind, we have our analytics set to (and have a headquarters in) the Central Time Zone in Austin, Texas. We like our conversion rate at 12 noon and 2pm, and clearly the conversion rate trails off in the evening after 4pm/5pm.

But even with this valuable data, our 12 noon is 1pm on the East Coast, and 12am on the West Coast.

Let’s Increase Our Accuracy With Segments

We want to see our hour of the day report for only those users actually in the same time zone. To do this, let’s create a custom segment in Google Analytics.

1. At the top of any report in Google Analytics, look above the chart and click “+ Add Segment”, you’ll find this right next to a button titled “All Users”. You’ll see the segment selection window:

Note that “All Users” is already selected in the segment selection window. That’s because technically, “All Users” is a segment, it is simply a segment with no filtering that allows all users in.

2. We could select an existing segment, but here, we’ll create one. To do so, click “New Segment”.  As a heads up, we are going to create a segment based on states that exist within the Central Standard Time Zone. Some states bleed into neighboring time zones, so we’ll fudge it. Here’s the screen where we create our segment, with a few fields filled in:

We’ve gotten started a bit with the previous screenshot. We’ve named our segment “CST Zone States”. Next we’ve made selections to the “Location” fields. “Region” lets us segment by states, and “Matches Regex” lets us use regular expressions to add states in series, with each state separated with a “|”, the pipe character. To add most of the states from the central time zone, you can enter the following into the Location/matches regex field:

Texas|Illinois|Oklahoma|Louisiana|Mississippi|Alabama|Kansas|Arkansas|Missouri|Indiana|Minnesota|Wisconsin

With this same technique, you can create segments that group cities together, group states together, or simply isolate particular geographic locations. Google Analytics Segments are very powerful tools and are commonly used by the best and the brightest.

Let’s Apply Our Segment to the Same Report

And when we are done with our segment, we simply click “Save”. Here is our new hour of the day conversion report.

A few facts become immediately apparent. First of all, we have a more stark difference between high-converting times during the work day and after hours. In fact, the period of 17:00 (5pm) to the workday morning is almost totally dead.  Keep in mind that when you work with segmented data, you might be substantially reducing your data set. In our case, we were now looking at only 30% of our total PPC traffic, and 1% or our total website traffic. If you over-segment, you’ll have tiny data sets and your insights won’t be meaningful.

Get Creative With Google Analytics Segments

You can do a lot with segments–essentially anything tracked in Google Analytics can be isolated and grouped with a segment. Just imagine: you can segment mobile users in Florida that arrived to your site via organic traffic. We use about 60 custom segments in our reporting to clients.